Abstract. Approximately 45% of the human genome is occupied by Mobile genetic Elements (MEs). Small subsets of these are still active and belong to three different families: L1, Alu, and SVA. These active families can generate new copies known as Mobile Element Insertions (MEIs), which can be polymorphic in humans. To find MEIs, large consortia have performed Whole Genome Sequencing (WGS) on a wide range of human populations and diseases, and designed computational tools to analyze the resulting data. One such effort, the 1000 Genomes Project (1KGP), performed WGS on 2,504 individuals from 26 different world populations to discover both MEIs and other human genetic variation. As part of the 1KGP, I designed an algorithm to find MEIs, the Mobile Element Locator Tool (MELT), and performed discovery for all active human ME families. While I found over 16,000 polymorphic MEIs, the 1KGP left several remaining open-ended questions about how these sites could affect human genetic diversity and impact human traits and diseases. For this proposal, I will work to answer some of these questions by designing new computational and sequencing tools. I will then use these tools to test the hypothesis that specific classes of MEs generate the majority of ME-derived genetic diversity among human populations and produce diseases such as cancer. I will approach this question using two aims. In Aim 1, I will develop computational tools to study how MEs have propagated in the human species. Then, I will adapt these tools to several non-human organisms to develop a model for ME mutagenesis and as a resource for the scientific community. Finally, I will use these new tools and one such model organism, canines, to understand ME distribution and propagation. In aim 2, I will develop sequencing tools to analyze a particularly active version of the L1 ME. Using this assay I will characterize a large number of active L1s, and subsequently associate these active L1s with ME activity in cancer. Overall, these studies will provide a better understanding of the relationship between MEs and human phenotypes and disease.